code: def update_hf_args(
      args: List[str], ds_config_dict: Dict[str, Any]
  ) -> List[str]:
      """
      Updates batch-size-related HF CLI args to be consistent with the values specified in the
      provided DeepSpeed config dictionary.
  
      Args:
          args: list of CLI arguments passed to the HF entrypoint
          ds_config_dict: the DeepSpeed configuration as a dictionary
      """
      hf_flag_to_ds_key = {
          "--per_device_train_batch_size": "train_micro_batch_size_per_gpu",
          "--gradient_accumulation_steps": "gradient_accumulation_steps",
      }
      # Overwrite CLI args
      args = copy.deepcopy(args)
      for idx in range(len(args)):
          if args[idx] in hf_flag_to_ds_key:
              ds_key = hf_flag_to_ds_key[args[idx]]
              overwrite_value = ds_config_dict[ds_key]
              # Need to avoid copying possible "auto" value from json config to HF CLI.
              is_auto = (
                  isinstance(overwrite_value, str)
                  and overwrite_value.strip() == "auto"
              )
              if not is_auto:
                  overwrite_value_str = str(overwrite_value)
                  if args[idx + 1] != overwrite_value_str:
                      logger.warning(
                          f"Changing {args[idx]} from {args[idx +1]} to {overwrite_value_str}"
                          " to match the deespspeed config values."
                      )
                      args[idx + 1] = overwrite_value_str
                  del hf_flag_to_ds_key[args[idx]]
  
      # Any remaining keys in hf_flag_to_ds_key were not provided as args to the HF CLI entrypoint,
      # but they must be added in explicitly, to avoid falling back to HF defaults.
      for hf_flag, ds_key in hf_flag_to_ds_key.items():
          hf_flag_value = ds_config_dict[ds_key]
          is_auto = (
              isinstance(hf_flag_value, str)
              and hf_flag_value.strip() == "auto"
          )
          if not is_auto:
              hf_flag_value_str = str(hf_flag_value)
              args.extend([hf_flag, hf_flag_value_str])
              logger.warning(
                  f"Adding {hf_flag} {hf_flag_value_str} to HF CLI args to reflect overwrite values."
              )
      return args
  
imports: import argparse
  import copy
  import json
  import logging
  import pathlib
  import random
  from contextlib import contextmanager
  from typing import Any, Dict, Generator, List, Optional, Union
  import filelock
  import torch
  import determined
  from determined.common import util
  from determined.pytorch.dsat import _defaults
  from determined.util import merge_dicts
label_desc: Use image node_id 14 for calling a global function with example usage: update_hf_args(args, ds_config_dict) and returns: args